N - mixture models by species

modelling N by site to get relative abundance

abundance by site will be used as a cov on predator occupancy

7 models evaluated, dot, jdt + jdtSQ, lure + jdt + jdtSQ


Species:      DouglasSquirrel



Metadata Summary:

N_sites N_counts N_detections rep_period iterations burnin thin
127 1467 386 7 days 120000 20000 10



Detections by Year:

Yr 2016 2017 2018 2019 2020
sites 19 31 19 32 26
detections 146 114 76 22 28
N.dot.model 20 28 22 9 24



WAIC

Models by WAIC:
model description WAIC N.total.est
fm7 counts 30.01311 127
fm1 dot 1654.77895 103
fm4 lure + jdt 1661.86163 109
fm6 lure + jdt + jdtSq 1662.81012 109
fm3 lure 1665.13588 118
fm2 jdt 1691.92470 140
fm5 jdt + jdtSq 1693.28732 140



Model summaries:



model: fm1
dot



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
p[1] NA 5298 0.329 0.332 0.28 0.39 0 1.001
p[2] NA 5278 0.168 0.167 0.13 0.21 0 1.001
p[3] NA 4557 0.096 0.094 0.07 0.12 0 1.001
p[4] NA 6856 0.081 0.077 0.05 0.12 0 1.001
p[5] NA 2441 0.033 0.03 0.01 0.05 0 1.0009
lambda[1] NA 8837 1.080 1.046 0.65 1.47 0 1.001
lambda[2] NA 7489 1.014 0.959 0.65 1.37 0 1.001
lambda[3] NA 6569 1.276 1.185 0.77 1.80 0 1.001
lambda[4] NA 8391 0.335 0.285 0.14 0.52 0 1.001
lambda[5] NA 1057 1.327 1.013 0.52 2.07 0 1.001
N[14] NA 8077 1.001 err 1.00 1.00 err err
N[19] NA 7341 1.122 err 1.00 2.00 err err
N[37] NA 8694 1.090 err 1.00 1.00 err err
N[49] NA 8053 0.001 err 0.00 0.00 err err
N[32] NA 10000 1.006 err 1.00 1.00 err err

p[1]

p[2]

p[3]

p[4]

p[5]

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[14]

N[19]

N[37]

N[49]

N[32]







model: fm2
jdt



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha jdt 10042 0.113 0.117 0.01 0.21 0.21728 0.957
alpha0 NA 4132 -2.193 -2.189 -2.36 -2.03 0 1.001
lambda[1] NA 6723 3.040 2.916 2.14 3.86 0 1.001
lambda[2] NA 7102 1.509 1.443 1.04 1.98 0 1.001
lambda[3] NA 9100 1.221 1.142 0.76 1.65 0 1.001
lambda[4] NA 10000 0.292 0.259 0.13 0.45 0 1.001
lambda[5] NA 10000 0.620 0.574 0.35 0.88 0 1.001
N[110] NA 9766 0.015 err 0.00 0.00 err err
N[7] NA 8357 6.303 7 5.00 9.00 0 1.001
N[102] NA 10000 0.008 err 0.00 0.00 err err
N[64] NA 10165 1.025 err 1.00 1.00 err err
N[34] NA 9638 2.223 2.002 1.00 3.00 0 1.0008

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[110]

N[7]

N[102]

N[64]

N[34]

alpha relationship







model: fm3
lure



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha lure 7275 -0.524 -0.517 -0.69 -0.37 0 1.001
alpha0 NA 4213 -2.228 -2.222 -2.40 -2.06 0 1.001
lambda[1] NA 7535 2.359 2.307 1.65 3.08 0 1.001
lambda[2] NA 7807 1.249 1.191 0.86 1.66 0 1.001
lambda[3] NA 8959 1.123 1.034 0.68 1.53 0 1.001
lambda[4] NA 10000 0.285 0.26 0.13 0.43 0 1.001
lambda[5] NA 10000 0.644 0.607 0.35 0.90 0 1.001
N[38] NA 10000 0.179 err 0.00 1.00 err err
N[13] NA 8674 2.381 2.002 2.00 4.00 0 1.0008
N[110] NA 9648 0.031 err 0.00 0.00 err err
N[59] NA 8489 3.453 3.002 3.00 5.00 0 1.0009
N[91] NA 8711 0.002 err 0.00 0.00 err err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[38]

N[13]

N[110]

N[59]

N[91]

alpha relationship







model: fm4
lure + jdt



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha[1] lureDays 6043 -0.628 -0.622 -0.79 -0.46 0 1.001
alpha[2] julianDt 7861 0.253 0.249 0.14 0.36 0.00139 1.0008
alpha0 NA 3861 -2.243 -2.237 -2.42 -2.06 0 1.001
lambda[1] NA 7004 2.009 1.961 1.36 2.67 0 1.001
lambda[2] NA 7688 1.199 1.148 0.78 1.56 0 1.001
lambda[3] NA 9099 1.135 1.05 0.70 1.55 0 1.001
lambda[4] NA 10000 0.286 0.25 0.13 0.45 0 1.001
lambda[5] NA 9695 0.695 0.636 0.38 0.97 0 1.001
N[56] NA 9538 1.293 1 1.00 2.00 0 1
N[8] NA 10000 0.059 err 0.00 0.00 err err
N[100] NA 10000 1.005 err 1.00 1.00 err err
N[82] NA 10000 0.036 err 0.00 0.00 err err
N[110] NA 8688 0.051 err 0.00 0.00 err err

alpha[1]

alpha[2]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[56]

N[8]

N[100]

N[82]

N[110]







model: fm5
jdt + jdtSq



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha[1] julianDt 2875 0.096 0.085 -0.09 0.29 0.759 0.7863
alpha[2] julianDtSq 3054 0.019 0.011 -0.15 0.20 0.99487 0.5722
alpha0 NA 3839 -2.190 -2.202 -2.36 -2.02 0 1.001
lambda[1] NA 6136 3.047 2.968 2.15 3.93 0 1.001
lambda[2] NA 6961 1.496 1.461 1.03 1.96 0 1.001
lambda[3] NA 8561 1.218 1.191 0.75 1.66 0 1.001
lambda[4] NA 10000 0.290 0.251 0.13 0.44 0 1.001
lambda[5] NA 10000 0.620 0.583 0.35 0.88 0 1.001
N[18] NA 9566 0.171 err 0.00 1.00 err err
N[17] NA 9186 1.231 err 1.00 2.00 err err
N[46] NA 10000 0.858 0 0.00 2.00 1 err
N[103] NA 10000 1.018 err 1.00 1.00 err err
N[120] NA 10000 1.016 err 1.00 1.00 err err

alpha[1]

alpha[2]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[18]

N[17]

N[46]

N[103]

N[120]

julian date relationship







model: fm6
lure + jdt + jdtSq



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha[1] lureDays 5868 -0.654 -0.655 -0.83 -0.49 0 1.001
alpha[2] julianDt 2641 0.374 0.355 0.17 0.57 0.01019 1
alpha[3] julianDtSq 2948 -0.133 -0.125 -0.32 0.04 0.51387 0.8768
alpha0 NA 4121 -2.247 -2.234 -2.43 -2.08 0 1.001
lambda[1] NA 6975 1.917 1.764 1.24 2.51 0 1.001
lambda[2] NA 7949 1.228 1.153 0.83 1.63 0 1.001
lambda[3] NA 9180 1.117 1.044 0.69 1.52 0 1.001
lambda[4] NA 10000 0.289 0.247 0.12 0.44 0 1.001
lambda[5] NA 8921 0.701 0.652 0.39 0.99 0 1.001
N[4] NA 7716 2.439 2.002 2.00 4.00 0 1.0009
N[58] NA 10000 0.011 err 0.00 0.00 err err
N[109] NA 10000 0.052 err 0.00 0.00 err err
N[56] NA 9628 1.279 1 1.00 2.00 0 1
N[51] NA 10000 0.156 err 0.00 1.00 err err

alpha[1]

alpha[2]

alpha[3]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[4]

N[58]

N[109]

N[56]

N[51]







model: fm7
counts



summary table

param covariate iters_ef mean mode hdi_89pct_lower hdi_89pct_upper bayes_P pct.density
alpha counts 9102 22.049 22.106 19.81 24.10 0 1.001
alpha0 NA 9544 -2.150 -2.123 -2.68 -1.59 0 1.001
lambda[1] NA 10000 0.995 0.941 0.60 1.37 0 1.001
lambda[2] NA 10000 0.984 0.949 0.61 1.33 0 1.001
lambda[3] NA 10405 0.976 0.918 0.55 1.39 0 1.001
lambda[4] NA 7090 0.866 0.696 0.37 1.37 0 1.001
lambda[5] NA 9695 0.972 0.909 0.54 1.38 0 1.001
N[31] NA 0 1.000 err 1.00 1.00 err err
N[104] NA 10000 0.946 0 0.00 2.00 1 err
N[52] NA 10000 0.904 0 0.00 2.00 1 err
N[124] NA 10000 1.024 err 1.00 1.00 err err
N[33] NA 10000 1.000 err 1.00 1.00 err err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[31]

## Warning in cor(X, use = "pairwise.complete.obs"): the standard deviation is zero
## Warning: Removed 50 rows containing missing values (geom_bar).

N[104]

N[52]

N[124]

N[33]

alpha relationship